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A robust and uncertainty-aware machine learning framework for PM2.5 prediction in a coastal urban Indian environment: implications for sustainable air quality management

Salvator Lawrence, Srimuruganandam Bhathmanabhan • Sustainable Environment Research (2026)

Abstract Accurate prediction of fine particulate matter (PM2.5) remains challenging because atmospheric processes are nonlinear, nonstationary, and influenced by temporal variability, measurement uncertainty, and episodic pollution events. ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s42834-026-00296-y

The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems

África Periáñez, Ana Fernández Del Río, Ivan Nazarov, Enric Jané et al. • Health Systems & Reform (2024)

Mobile health has the potential to revolutionize health care delivery and patient engagement. In this work, we discuss how integrating Artificial Intelligence into digital health applications focused on supply chain operation, patient manag...

DOAJ Open Access (DOAJ) DOI: 10.1080/23288604.2024.2387138

Developing an Interferogram-Based Module with Machine Learning for Maintaining Leveling of Glass Substrates

Syuan-Cheng Chang, Chung-Ping Chang, Yung-Cheng Wang, Chi-Chieh Chu • Machines (2023)

In this research, we propose a method that utilizes machine learning to maintain the parallelism of the resonant cavity in a Fabry–Perot interferometer designed specifically for glass substrates. Based on the optical principle and theory, w...

DOAJ Open Access (DOAJ) DOI: 10.3390/machines11060668

User perspectives on AI explainability in aerospace manufacturing: a Card-Sorting study

Sofia Morandini, Federico Fraboni, Mark Hall, Santiago Quintana-Amate et al. • Frontiers in Organizational Psychology (2025)

The integration of AI technologies in aerospace manufacturing is significantly transforming critical operational processes, impacting decision-making, efficiency, and workflow optimization. Explainability in AI systems is essential to ensur...

DOAJ Open Access (DOAJ) DOI: 10.3389/forgp.2025.1538438

MRI Application in Quantification of Epiphyseal Development in the Wrist and Bone Age Estimation of Han Male Adolescents in East China

ZHOU Zhi-lu, ZHANG Dong-fei, CHEN Jie-min, WANG Ya-hui et al. • Fayixue Zazhi (2024)

ObjectiveTo investigate the value of wrist MRI in bone age estimation for male adolescents in Shanghai, Zhejiang and Jiangsu.MethodsA total of 124 Han male adolescents aged 6.0 to 18.0 years from Shanghai, Zhejiang and Jiangsu were selected...

DOAJ Open Access (DOAJ) DOI: 10.12116/j.issn.1004-5619.2023.231203

Design Recommendations for Immersive Virtual Reality Application for English Learning: A Systematic Review

Jessica Rodrigues Esteves, Jorge C. S. Cardoso, Berenice Santos Gonçalves • Computers (2023)

The growing popularity of immersive virtual reality (iVR) technologies has opened up new possibilities for learning English. In the literature, it is possible to find several studies focused on the design, development, and evaluation of imm...

DOAJ Open Access (DOAJ) DOI: 10.3390/computers12110236

Adopting AI Enhances Humanitarian Operations While Demanding Critical Trade-Offs

Caroline Grangier, Munzer Alkhalil, Aula Abbara • Avicenna Journal of Medicine (2026)

Artificial intelligence (AI) is increasingly impacting the cooperation sector, transforming how humanitarians are operating in the field. AI tools now allow for improved health diagnostics and quality services. In conflict areas, organizati...

DOAJ Open Access (DOAJ) DOI: 10.1055/s-0046-1822817

Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis

Hamidreza Amiri, Samira Peiravi, Seyedeh sara rezazadeh shojaee, Motahareh Rouhparvarzamin et al. • BMC Medical Education (2024)

Abstract Background Nowadays, Artificial intelligence (AI) is one of the most popular topics that can be integrated into healthcare activities. Currently, AI is used in specialized fields such as radiology, pathology, and ophthalmology. Des...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12909-024-05406-1

Deep learning-based multimodal data fusion in bone tumor management: Advances in clinical decision support

Tongtong Huo, Wei Wu, Xiaoliang Chen, Mingdi Xue et al. • Intelligent Oncology (2025)

Bone tumors (BTs)—including osteosarcoma, Ewing sarcoma, and chondrosarcoma—are rare but biologically complex malignancies characterized by pronounced heterogeneity in anatomical location, histological subtype, and molecular alterations. Re...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.intonc.2025.06.005

Automated measurement of CD8+ T-cell distribution at the tumor epithelial–stromal interface is associated with NSCLC immunotherapy benefit and transcriptomic pathways

Patrick Leo, Hauke Kolster, Hartmut Koeppen, Jennifer Giltnane et al. • Journal of Pathology Informatics (2026)

Whereas anti-PD-(L)1 therapies are widely used in cancer treatment, only a subset of patients achieve long-term survival. Companion diagnostics based on PD-L1 expression have limited predictive power for these therapies, motivating developm...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jpi.2026.100688

Development and validation of an interpretable machine learning model for predicting the risk of coronary heart disease risk in diabetes mellitus patients: a dual-center retrospective study

Ye Kuang, Yan Yu, Jing Li, Chuanmei Peng et al. • BMC Medical Informatics and Decision Making (2026)

Abstract Background Diabetes mellitus (DM) combined with coronary heart disease (CHD) significantly increases the risk of cardiovascular events with a greater mortality rate. Therefore, establishing a predictive model can help DM patients r...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-026-03461-w

Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics

Alireza Kasaie, Suchithra Rajendran • Healthcare Analytics (2023)

This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care. We develop and compare four machine learning models, including multinomial logistic regression, decision ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100242

A novel and accelerated method for integrated alignment and variant calling from short and long reads

Jinnan Hu, Donald Freed, Hanying Feng, Hong Chen et al. • Frontiers in Bioinformatics (2026)

BackgroundIntegrating short- and long-read sequencing technologies has become a promising approach for achieving accurate and comprehensive genomic analysis. Although short-read sequencing (Illumina, etc.) offers high base accuracy and cost...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbinf.2025.1691056

Artificial Intelligence, Green Innovation, and the Clean-Energy Market: A Quantile-Based Analysis

Dervis Kirikkaleli, Seyed Alireza Athari, Mohamed Djafar Henni, Emmanuel Oluwatosin Adewusi et al. • Energies (2026)

Artificial intelligence is increasingly viewed as both a catalyst for clean-energy development and a potential constraint on green innovation. This study examines the quantile-specific relationships between artificial intelligence, clean-en...

DOAJ Open Access (DOAJ) DOI: 10.3390/en19184397

COGNITIVE FEATURES OF MANAGERIAL DECISION MAKING IN TERMS OF THE DIGITAL ECONOMY. THE RESULTS OF EXPERIMENT

V. V. Degtyareva, D. A. Sozaeva • Вестник университета (2019)

The transformation of managerial decision-making processes in the digital economy, the modification of the boundaries of the personal space of an employee and manager (manager) when making collegial decisions through social networks and oth...

DOAJ Open Access (DOAJ) DOI: 10.26425/1816-4277-2019-4-5-13